Bibliographic record
Abstract
Purpose – Living wage campaigns are popular responses to counter increasing inequality in advanced industrial countries. The purpose of this paper is to examine how voluntary living wage employer certification engages business in multi-sectoral coalitions to reduce poverty. Design/methodology/approach – The authors utilize qualitative interviews with 30 members of a living wage employer certification program in Vancouver, Canada as a case study to explore campaign participation by the business community and business case outcomes. Findings – Certifying voluntary living wage employers engaged business community members as partners and advocates in a living wage campaign. Certified living wage employers fulfilled business case projections for worker compensation fairness, human resource improvements and corporate branding advantages. Research limitations/implications – The study focussed on the early stages of a living wage employer certification program. As the number of living wage certification programs and ordinances grows, future research would benefit from examining how different social policy contexts in other Canadian and international regions affects whether these two avenues support one another or one avenue becomes favoured. Originality/value – Most studies of living wage campaigns have not dealt with how voluntary employer certification programs affect campaign participation and outcomes. The approach the authors adopt in the case takes into account the role of voluntary employer certification programs on campaign participation by the business community and business case outcomes. The study findings are of value to businesses, activists and policy analysts, who engage in or study corporate social responsibility initiatives to facilitate the creation of “good jobs” that provide family sustaining wages and benefits, particularly to lower-tier workers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".